A second purpose is to improve a network’s performance on images from a particular camera. A typical approach is to augment labeled data from the specific camera with synthetic data. A number of different methods are available to make synthetic images match existing camera images. For example, style transfer has been used [1]} and networks have been proposed to generate synthetic scenes that match the scenes in a specific dataset [2]}, [3]}. The objective is to reduce the burden of acquiring and labeling new training data. This approach synthesizes images as a form of domain adaptation.
